INTELLIGENT DECISION SUPPORT SYSTEMS: METHODS FOR OPTIMIZING AND SUPPORTING MANAGEMENT DECISIONS
Keywords:
bio-inspired algorithms, multi-agent systems, hybrid systems, reliability, efficiency, decision support systems, information systems, destabilizing factors, levels of functioning, integrated modeling, artificial neural networks, enhanced genetic algorithm, metaheuristic algorithmSynopsis
The high dynamism of the development of social processes and phenomena determines the formation of new systems of humanity's worldview, modification (change) of the hierarchy of needs and values, challenges to the pace and quality of development.
Addressing the over-complicated problems associated with meeting the demands of modern times requires the application of innovative scientific approaches. Today, the use of modern intelligent technologies such as artificial neural networks, deep learning and artificial intelligence is a prerequisite for the active development of all spheres of human activity: medicine, technology, business, environmental protection, education, transport and communication, etc.
Thus, it is the intellectualization of technical and management systems that can be considered one of the key bases of the new paradigm of science and technology. The phrase “of the artificial intelligence system is clear and known to everyone today. The context of this term is associated with concepts such as robotics, forecasting, processing of large information flows, expert systems, diagnostics, projects “smart house” or “smart tools”, cyber-physical space and cyber-physical systems, computer translation, etc.
There is a positive dynamics of the development and implementation of elements of artificial intelligence in most types of software: mobile applications, information systems, electronic devices, etc.
This process of “intellectualization” allows to talk about the gradual increase in the intelligence of modern computer systems capable of performing functions that are traditionally considered intellectual: understanding language, logical inference, using accumulated knowledge, learning, pattern recognition, as well as learning and explaining your decisions.
The monograph contains methods of processing heterogeneous data, a scientific-methodical apparatus for assessing the state of complex technical systems, as well as a scientific-methodical apparatus for ensuring the functional reliability of special purpose information systems.
Separate chapters present mathematical models of the functioning of information systems under the influence of a set of destabilizing factors, as well as a polymodel complex of resource management of intelligent decision support systems. The specified polymodel complexes allow modeling of the functioning process of intelligent decision support systems and information systems. This is important when modeling the processes of solving complex calculation tasks in the specified systems due to the conceptual description of the specified processes.
The authors' research is supported by appropriate analytical expressions, graphic dependencies, as well as tabular values.
The monograph will be useful for researchers dealing with issues of solving optimization problems, using the theory of artificial intelligence, developing new (improving existing) approaches to solving complex technical problems in various fields of human activity.
The monograph is also useful for practitioners – designers, developers implementing modern solutions in the field of information technologies, engaged in the development of information, information-analytical, as well as automated systems for the purpose of creating new schemes and algorithms, their adaptation to non-stereotypical conditions of use, including for the implementation of artificial intelligence methods in conditions of autonomous operation, limitation of computing resources, remote control, etc.
Chapters
References
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Published
January 15, 2026
Categories
Copyright (c) 2026 Yurii Zhuravskyi, Dmytro Fedorchuk, Oleksandr Perehuda, Mykola Romanchuk, Roman Stavisiuk, Dmytro Stupak, Serhii Neronov, Ganna Plekhova, Olena Feoktystova, Igor Shostak, Anastasiia Voznytsia, Andrii Shyshatskyi, Danylo Pliekhov, Oleksii Nalapko, Yuliia Vakulenko, Andrii Lebedynskyi, Oksana Dmytriieva, Ivan Starynskyi, Oleksandr Zhuk, Pavlo Zhuk, Andrii Veretnov, Olena Shaposhnikova, Yaroslav Melnyk, Oleh Shknai, Illia Dmytriiev, Oleg Sova, Olesia Zhuk, Bohdan Molodetskyi
How to Cite
Zhuravskyi, Y. (Ed.). (2026). INTELLIGENT DECISION SUPPORT SYSTEMS: METHODS FOR OPTIMIZING AND SUPPORTING MANAGEMENT DECISIONS. Kharkiv: TECHNOLOGY CENTER PC. https://doi.org/10.15587/978-617-8360-23-8
